An ℋ approach to stability analysis of switched Hopfield neural networks with time-delay

Research output: Contribution to journalArticle

57 Citations (Scopus)

Abstract

This paper proposes a new ℋ weight learning law for switched Hopfield neural networks with time-delay under parametric uncertainty. For the first time, the ℋ weight learning law is presented to not only guarantee the asymptotical stability of switched Hopfield neural networks, but also reduce the effect of external disturbance to an ℋ norm constraint. An existence condition for the ℋ weight learning law of switched Hopfield neural networks is expressed in terms of strict linear matrix inequality (LMI). Finally, a numerical example is provided to illustrate our results.

Original languageEnglish
Pages (from-to)703-711
Number of pages9
JournalNonlinear Dynamics
Volume60
Issue number4
DOIs
Publication statusPublished - 2010 Jun 1
Externally publishedYes

Fingerprint

Hopfield neural networks
Hopfield Neural Network
Stability Analysis
Time Delay
Time delay
Asymptotical Stability
Parametric Uncertainty
Linear matrix inequalities
Matrix Inequality
Linear Inequalities
Disturbance
Norm
Numerical Examples
Learning

Keywords

  • ℋ stability
  • Linear matrix inequality (LMI)
  • Lyapunov-Krasovskii stability theory
  • Switched Hopfield neural networks
  • Weight learning law

ASJC Scopus subject areas

  • Applied Mathematics
  • Mechanical Engineering
  • Aerospace Engineering
  • Ocean Engineering
  • Electrical and Electronic Engineering
  • Control and Systems Engineering

Cite this

An ℋ approach to stability analysis of switched Hopfield neural networks with time-delay. / Ahn, Choon Ki.

In: Nonlinear Dynamics, Vol. 60, No. 4, 01.06.2010, p. 703-711.

Research output: Contribution to journalArticle

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